Predictive Fidelity Interpretability and Resilience of Machine Learning Methods Applied to Scientific Simulations.
Conference
·
OSTI ID:1508933
Abstract not provided.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1508933
- Report Number(s):
- SAND2017-8865C; 656355
- Resource Relation:
- Conference: Proposed for presentation at the DOE ASCR PI meeting held September 11-12, 2017 in Rockville, MD.
- Country of Publication:
- United States
- Language:
- English
Similar Records
Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.
Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.
Estimating Predictive Uncertainty in Scientific Machine Learning: A Library of Methods and Test Problems.
Conference
·
Mon Jan 01 00:00:00 EST 2018
·
OSTI ID:1508933
+3 more
Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.
Conference
·
Mon Jan 01 00:00:00 EST 2018
·
OSTI ID:1508933
+3 more
Estimating Predictive Uncertainty in Scientific Machine Learning: A Library of Methods and Test Problems.
Conference
·
Wed Jul 01 00:00:00 EDT 2020
·
OSTI ID:1508933